Model‐Based Prediction of Clinically Relevant Thrombocytopenia after Allogeneic Hematopoietic Stem Cell Transplantation

Platelet reconstitution after allogeneic hematopoietic cell transplantation (allo-HCT) is heterogeneous and influenced by various patient- and transplantation-related factors, associated with poor prognoses for poor graft function (PGF) and isolated thrombocytopenia. Tailored interventions could improve the outcome of patients with PGF and post-HCT thrombocytopenia. To provide individual predictions of 180-day platelet counts from early phase data, we developed a model of long-term platelet reconstitution after allo-HCT. A large cohort (n = 1949) of adult patients undergoing their first allo-HCT was included. Real-world data from 1,048 retrospective patients were used for non-linear mixed-effects model development. Bayesian forecasting was used to predict platelet-time profiles for 518 retrospective and 383 prospective patients during internal and external model validation, respectively. Thrombocytopenia was defined as mean platelet count < 75 × 10<sup>9</sup>/L, derived from the last 12 platelet measurements within the first 180 days post-HCT. Thrombocytopenia affected 37% of all patients and was associated with significantly reduced overall survival (P-value < 0.0001). On days +7, +14, +21, and +28, the developed model achieved areas under the receiver-operating characteristic of ≥ 0.68, ≥ 0.75, ≥ 0.78, and 0.81 for the prediction of post-HCT thrombocytopenia, respectively, with anti-thymocyte globulin, donor relation, and total protein measurements representing prognostic markers for post-HCT platelet kinetics. A publicly accessible web-based demonstrator of the model was established (https://hsct.precisiondosing.de). In summary, the developed model predicts individual platelet counts from day +28 post-HCT adequately, utilizing internal and external datasets. The web-based demonstrator provides a basis to implement model-based predictions in clinical practice and to confirm these findings in future clinical studies.

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Publication Details

Journal
Clinical Pharmacology & Therapeutics
Published
2025-02-06
DOI
https://doi.org/10.1002/cpt.3580
Primary Topic
Platelet Disorders and Treatments
Type
article
Field-Weighted Citation Impact
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article

Model‐Based Prediction of Clinically Relevant Thrombocytopenia after Allogeneic Hematopoietic Stem Cell Transplantation

Jürgen Rissland, Stephan Kiefer, Ulf Schwarz, Joerg Thomas Bittenbring et al.
Clinical Pharmacology & Therapeutics
Platelet Disorders and Treatments
article

Model‐Based Prediction of Clinically Relevant Thrombocytopenia after Allogeneic Hematopoietic Stem Cell Transplantation

Jürgen Rissland, Stephan Kiefer, Ulf Schwarz, Joerg Thomas Bittenbring, Dietrich W. Beelen, Katharina M. Götz, Dominik Selzer, Christian Brossette, Katharina Och, Norbert M. Graf, Sigrun Smola, Lisa Eisenberg, Dominic Kaddu‐Mulindwa, Amin T. Turki, Matthias Schwab, Simeon Rüdesheim, Kerstin Rohm, Gabriele Weiler, Nico Pfeifer, Thorsten Lehr, Jochen Rauch, Claudia Riede, Yvonne Braun, Stefan Theobald
article en

Abstract

Platelet reconstitution after allogeneic hematopoietic cell transplantation (allo-HCT) is heterogeneous and influenced by various patient- and transplantation-related factors, associated with poor prognoses for poor graft function (PGF) and isolated thrombocytopenia. Tailored interventions could improve the outcome of patients with PGF and post-HCT thrombocytopenia. To provide individual predictions of 180-day platelet counts from early phase data, we developed a model of long-term platelet reconstitution after allo-HCT. A large cohort (n = 1949) of adult patients undergoing their first allo-HCT was included. Real-world data from 1,048 retrospective patients were used for non-linear mixed-effects model development. Bayesian forecasting was used to predict platelet-time profiles for 518 retrospective and 383 prospective patients during internal and external model validation, respectively. Thrombocytopenia was defined as mean platelet count < 75 × 10<sup>9</sup>/L, derived from the last 12 platelet measurements within the first 180 days post-HCT. Thrombocytopenia affected 37% of all patients and was associated with significantly reduced overall survival (P-value < 0.0001). On days +7, +14, +21, and +28, the developed model achieved areas under the receiver-operating characteristic of ≥ 0.68, ≥ 0.75, ≥ 0.78, and 0.81 for the prediction of post-HCT thrombocytopenia, respectively, with anti-thymocyte globulin, donor relation, and total protein measurements representing prognostic markers for post-HCT platelet kinetics. A publicly accessible web-based demonstrator of the model was established (https://hsct.precisiondosing.de). In summary, the developed model predicts individual platelet counts from day +28 post-HCT adequately, utilizing internal and external datasets. The web-based demonstrator provides a basis to implement model-based predictions in clinical practice and to confirm these findings in future clinical studies.

Clinical Pharmacology & TherapeuticsVol. 117(5)
University Hospitals of the Ruhr-University of Bochum (DE), Essen University Hospital (DE), Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology (DE), Averbis (Germany) (DE), Fraunhofer Institute for Biomedical Engineering (DE), University of Tübingen (DE), Ruhr University Bochum (DE), Saarland University (DE)
European Commission, Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung, HORIZON EUROPE Framework Programme
No poverty
Openalex Percentile: Top 97%
Platelet Disorders and Treatments
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